Techniques for Updating Filter Coefficients of an Adaptive Filter

ABSTRACT

A technique for updating filter coefficients of an adaptive filter includes filtering a signal with an adaptive filter, whose filter coefficients are grouped into filter blocks. In this case a number of the filter blocks is less than or equal to a number of the filter coefficients. During each update period, the filter coefficients for less than all of the filter blocks are updated based on a network echo path impulse response.

BACKGROUND

1. Field

This disclosure relates generally to an adaptive filter and, morespecifically, to techniques for updating filter coefficients of anadaptive filter.

2. Related Art

Echo cancellation is used in communication systems to remove echo from avoice communication in order to improve voice quality. Echo cancellationinvolves first recognizing an originally transmitted signal thatre-appears, with some delay and linear modification, in a transmitted orreceived signal. More particularly, a signal affected by the phenomenonof echo produced by the presence of a hybrid circuit and/or acousticalcoupling between a mouth-piece and an ear-piece is the signal travellingfrom the near-end to the far-end. If the point of reference is thenear-end part of the connection, then the signal affected corresponds tothe transmitted signal. If the point of reference is the far-end part ofthe connection, then the signal affected corresponds to the receivedsignal. Upon recognition, an echo can be removed by subtracting the echofrom a transmitted or received signal. Echo cancellation can beimplemented using a digital signal processor (DSP).

Two primary sources of echo in telephony are acoustic echo and hybridecho. Acoustic echo arises when sound from a speaker of a telephonehandset is picked up by a microphone of the telephone handset. Forexample, acoustic echo may occur in conjunction with hands-free carphone systems, a standard telephone in speakerphone or hands-free mode,conference telephones, installed room systems that use ceiling speakersand table-top microphones, video conferencing systems, etc. Directacoustic path echo is attributable to sound from a speaker of a handsetthat enters a microphone of the handset substantially unaltered. Whenindirect acoustic path echo (reverberation) occurs, the echo can bedifficult to effectively cancel (unlike echo associated with a directacoustic path) as the original sound is altered by ambient space. Thealtered echo may be attributed to certain frequencies being absorbed bysoft furnishings and reflection of different frequencies at varyingstrength.

Acoustic echo cancellers are usually designed to deal with changes andadditions to an original signal caused by imperfections of a speaker,imperfections of a microphone, reverberant space, and physical coupling.In general, acoustic echo cancellation (AEC) algorithms approximateresults of a next sample by comparing the difference between current andone or more previous samples. The information has then been used topredict how sound is altered by an acoustic space. In this case, themodel of the acoustic space is continually updated. The changing natureof a sampled signal is mainly due to changes in the acousticenvironment, not changes in the characteristics of a loudspeaker, amicrophone, or physical coupling. That is, changes in a sampled signalare usually attributable to objects moving in an acoustic environmentand movement of a microphone within the environment. For example, when adoor is closed or opened, a chair is pulled in closer to a table, ordrapes are opened or closed a change in reverberation of sound in anacoustic space occurs. To address changes in acoustic space, an echocancellation algorithm may employ non-linear processing (NLP), whichallows an algorithm to make changes to an acoustic space model that aresuggested (but not yet confirmed) by signal comparison.

Hybrid (electric) echo is generated in public switched telephonenetworks (PSTNs) or in packet networks as a result of the reflection ofelectrical energy by a hybrid circuit. Hybrid echo may also be generatedin voice-over-packet network systems, if the systems contain networkelements (such as access gateways) that are equipped with access loopinterfaces. As is known, most telephone local loops are two-wirecircuits, while transmission facilities are usually four-wire circuits.A hybrid circuit or hybrid (typically, a part of an electronic devicecalled a subscriber line interface circuit (SLIC)) converts a signalbetween the two-wire and four-wire circuits. Unfortunately, when animpedance mismatch occurs, a hybrid produces a hybrid echo signal. Anadaptive filter (included in a line echo canceller or a network echocanceller) learns about characteristics of the hybrid during anadaptation process. The output signal from the adaptive filter isinverted and combined with the hybrid echo signal. When the adaptationprocess is performed correctly, the result of combination of the hybridecho signal and the inverted output signal of the adaptive filterproduces a very small signal (called an error signal). Ideally, theerror signal is small such that the error signal is not perceivedaudibly.

An adaptive filter is a filter that self-adjusts its transfer functionaccording to an optimizing algorithm. Due to the complexity of mostoptimizing algorithms, adaptive filters are usually implemented asdigital filters using DSPs, which modify their filter coefficients basedon an input signal. As the power of DSPs has increased, adaptive filtershave become more common and are now routinely used in various devices,e.g., echo cancellers, mobile phones and other communication devices,camcorders and digital cameras, and medical monitoring equipment.

A relatively long adaptive filter is required for some line connectionsand/or access system configurations in order to cancel echo adequately.In general, long adaptive filters have a relatively high computationalcost and are slow to converge. However, when a pure delay estimator isemployed in conjunction with an adaptive filter, a shorter adaptivefilter can usually be employed to model an active portion of a networkecho path impulse response. In practice, the adaptation process usuallynever produces an ideal characteristic of the hybrid and the errorsignal is often so large that other approaches for reducing the errorsignal are needed. As mentioned above, a typical method of reducing theenergy of the error signal is based on NLP.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and is notlimited by the accompanying figures, in which like references indicatesimilar elements. Elements in the figures are illustrated for simplicityand clarity and have not necessarily been drawn to scale.

FIG. 1 is a diagram of a relevant portion of an example communicationsystem (which carries voice communications and may carry data) thatincludes an echo canceller, configured according to an embodiment of thepresent invention.

FIG. 2 is a diagram of a relevant portion of an example echo canceller,configured according to an embodiment of the present invention.

FIG. 3 is a flowchart of an example process for updating filtercoefficients of an adaptive filter employed in an echo canceller of acommunication system, according to various embodiments of the presentinvention.

DETAILED DESCRIPTION

In the following detailed description of exemplary embodiments of theinvention, specific exemplary embodiments in which the invention may bepracticed are described in sufficient detail to enable those skilled inthe art to practice the invention, and it is to be understood that otherembodiments may be utilized and that logical, architectural,programmatic, mechanical, electrical and other changes may be madewithout departing from the spirit or scope of the present invention. Thefollowing detailed description is, therefore, not to be taken in alimiting sense, and the scope of the present invention is defined onlyby the appended claims and their equivalents. In particular, althoughthe preferred embodiment is described below in conjunction withtechniques for adjusting filter coefficients of an adaptive filterincluded in an echo canceller, it will be appreciated that the presentinvention may find application in various devices (in a wired orwireless communication system) that include a filter whose filtercoefficients require adjustment.

As used herein, the term ‘coupled’ includes a direct electricalconnection between elements or components and an indirect electricalconnection between elements or components achieved using one or moreintervening elements or components. As is also used herein, “Sin signal”refers to a send input (Sin) signal received from a near-end at a Sinport of an echo canceller, “Rout signal” refers to a receive output(Rout) signal provided to the near-end at an Rout port of the echocanceller, “Sout signal” refers to a send output (Sout) signal providedto a far-end at an Sout port of the echo canceller, “Rin signal” refersto a receive input (Rin) signal received from the far-end at an Rin portof an echo canceller and “Sgen signal” refers to a send generated (Sgen)signal generated by a communication device at the near-end.

As noted above, when a pure delay estimator is employed in conjunctionwith an adaptive filter, a shorter adaptive filter can usually beemployed to model an active portion of a network echo path impulseresponse. Today, a typical network echo canceller that is compliant withthe ITU-T G.168 digital echo canceller standard may employ a twenty-four(24) millisecond adaptive filter. Per the ITU-T G.168 digital echocanceller standard, filter coefficients with relatively large valuesoccupy significantly less than twenty-four milliseconds. In general,filter coefficients with small values, while being relatively importantto final convergence, contribute little to initial convergence.

According to the present disclosure, techniques are employed thatsegment an impulse response into multiple filter blocks, each of whichmay be updated at a different frequency. In general, the techniques areapplicable to network echo path characteristics specified in the ITU-TG.168 digital echo canceller standard. It should, however, beappreciated that the techniques disclosed herein may be broadly appliedto updating filter coefficients of adaptive filters employed in variousapplications given a known network echo path model.

According to the present disclosure, an adaptive filter is segmentedinto ‘N’ (N≦K, where ‘K’ is the number of (mite impulse response (FIR)time-domain filter coefficients) filter blocks, each of which may havethe same or a different length. For each iteration or input sample, only‘M’ filter blocks (where M<N) are selected to be updated and filtercoefficients in unselected filter blocks remain unchanged. The choice ofwhich filter block or blocks to update depends on the characteristics ofthe G.168 specified network echo path model. In general, filter blockswith significant filter coefficients are updated more frequently thanfilter blocks with less significant filter coefficients. As only aportion of the filter coefficients (of an adaptive filter) are updatedeach iteration or input sample, less computational power is required. Ingeneral, the initial convergence degradation is minimal, as (by design)only relatively small filter coefficients are partially updated (i.e.,not updated every input sample). The techniques disclosed herein usuallydecrease the million clock cycles per second (MCPS) consumption of anadaptive filter implemented within a DSP. Typically, an echo cancellerthat employs an adaptive filter with a lower MCPS consumption is lessexpensive and may provide additional channels that may be utilized toimplement additional features.

As one example, an echo canceller may implement an adaptive filter withone-hundred ninety-two filter coefficients that is segmented into threefilter blocks, with sixty-four coefficients (8 ms) each. In thisexample, a first block (that includes filter coefficients 1-64, whichare the most significant filter coefficients) is updated every inputsample. A second block (that includes filter coefficients 65-128, whichare less significant filter coefficients) is updated every odd inputsample and a third block (including filter coefficients 129-192, whichare less significant filter coefficients) is updated every even inputsample. In this case, the MCPS saving is about thirty-three percent.

As another example, an echo canceller may implement an adaptive filterwith one-hundred ninety-two filter coefficients that is segmented intothree blocks as follows: a first block having ninety-six coefficients(12 ms); and second and third blocks each including forty-eightcoefficients (6 ms). In this case, the first block (including filtercoefficients 1-96, which are the most significant filter coefficients)may be updated every input sample, the second block (including filtercoefficients 97-144, which are less significant filter coefficients) maybe updated every odd input sample, and the third block (including filtercoefficients 145-192, which are less significant filter coefficients)may be updated every even input sample. In this case, the MCPS saving isabout twenty-five percent. It should be appreciated that a variety ofother combinations may be employed based on overall system tuningrequirements. It should also be appreciated that the techniquesdisclosed herein can be used with virtually any adaptive filteringalgorithm (e.g., an affine projection (AP) algorithm, a normalized leastmean squares (NLMS) algorithm, a least mean squares (LMS) algorithm, ora recursive least squares (RLS) algorithm).

According to one aspect of the present disclosure, a technique forupdating filter coefficients of an adaptive filter includes filtering asignal with an adaptive filter, whose filter coefficients are groupedinto filter blocks. In this case a number of the filter blocks is lessthan or equal to a number of the filter coefficients. During each updateperiod, the filter coefficients for less than all of the filter blocksare updated based on a network echo path impulse response.

According to one aspect of the present disclosure, a communicationdevice includes a control module and an adaptive filter that is incommunication with the control module. The adaptive filter is configuredto filter a signal and is segmented into filter blocks. In this case, anumber of the filter blocks is less than or equal to a number of filtercoefficients for the adaptive filter. The filter coefficients aregrouped into the filter blocks based on a network echo path impulseresponse and, during each update period, the filter coefficients forless than all of the filter blocks are updated.

According to another aspect of the present disclosure, a method forupdating filter coefficients of an adaptive filter of an echo cancellerincludes filtering an echo signal with an adaptive filter, whose filtercoefficients are grouped into filter blocks based on a network echo pathimpulse response. In this case, a number of the filter blocks is lessthan or equal to a number of the filter coefficients. During each updateperiod, the filter coefficients for less than all of the filter blocksare updated based on a metric associated with the filter coefficients.

With reference to FIG. 1, an example communication system 10 isillustrated that includes echo cancellers that are configured accordingto the present disclosure. The system 10 includes a transmitter/receiver12, an interface 13 (which includes hybrid circuit (hybrid) 16), anexample echo canceller 20, a tone detector 50, a communication network24, an example echo canceller 22, a tone detector 52, an interface 15(which includes hybrid 18), and a transmitter/receiver 14. Thetransmitter/receiver 12 is coupled to the hybrid 16 (e.g., via atwo-wire connection such as a twisted pair of wires), which is coupledto the echo canceller 20. The hybrid 16 provides a send input (Sin)signal 37 to the echo canceller 20 (on an Sin port) and receives areceive output (Rout) signal 40 from the echo canceller 20 (on an Routport). The Sin signal 37 and the Rout signal 40 may be, for example,provided and received via a wire pair. The echo canceller 20 is coupledto the network 24 and provides an echo canceller send output (Sout)signal 42 to the network 24 (on an Sout port) and receives a receiveinput (Rin) signal 43 from the network 24 (on an Rin port). An output ofthe echo canceller 20 is also coupled to an input of the tone detector50 and provides an error signal 46 to the input of the tone detector 50.

Similarly, the transmitter/receiver 14 is coupled to the hybrid 18,which is coupled to the echo canceller 22, which is coupled to thenetwork 24. The echo canceller 22 also provides an echo cancelled Soutsignal to the network 24 and receives a Rin signal from the network 24.The echo canceller 22 also provides an error signal to the tone detector52. A control bus (control) 17 carries one or more control signals thatare provided to each component of the system 10 or a subset of thecomponents of the system 10. In operation, the transmitter/receiver 12provides communication signals to and receives communication signalsfrom the hybrid 16. The transmitter/receiver 12 can be virtually anydevice (e.g., a telephone or a modem) used for communicating over thenetwork 24. The transmitter/receiver 14 and the hybrid 18 function in asimilar manner as the transmitter/receiver 12 and the hybrid 16,respectively, and for brevity are not discussed in detail herein.

In communications between the transmitter/receiver 12 and thetransmitter/receiver 14, electric or hybrid echo may be introduced bythe hybrids 16 and 18. As previously noted, the source of the echo isthe impedance mismatch between the hybrids 16 and 18 and the network 24.For example, if the impedance within the hybrid 16 perfectly matched theimpedance of the network 24, all of the energy from the Rout signal 40would be transmitted to the transceiver/receiver 12. However, when animpedance mismatch exists, some of the energy from the Rout signal 40 isreflected back through the Sin signal 37. If the round trip delaythrough the network 24 (e.g., from/to the transmitter/receiver 14 in thecase of echo introduced by the hybrid 16) is sufficiently long, thereflected echo received by the transmitter/receiver 14 will benoticeable during the communication. The round trip delay may result innoticeable echoes or even unbearable disturbance during a telephonevoice communication.

For example, a sufficiently long delay may correspond to a round tripdelay of greater than forty (40) milliseconds. If, on the other hand,the round trip delay is significantly smaller, the echo may not bedisruptive since it may be indistinguishable from a side tone. The roundtrip delay may include a variety and/or combination of different delays,e.g., a transmission delay, a processing delay, and/or a computationdelay. Depending on the communication system, the round trip delay maybe sufficiently large to disrupt communication. In various embodiments,the echo cancellers 20 and 22 are implemented to reduce echo in thesystem 10 to a manageable level. For example, the echo introduced by thehybrid 16 from a signal received via the Rout signal 40 (from thetransmitter/receiver 14) and reflected back (to the transmitter/receiver14) via the Sin signal 37 is processed by the echo canceller 20 toreduce the reflected echo prior to sending the Sout signal 42 (throughthe network 24) to the transmitter/receiver 14.

The tone detector 50 is configured to receive an error signal 46 (fromthe echo canceller 20) and perform tone detection (on the error signal46) to determine if a tone (e.g., a dial-tone or a dual-tone multiplefrequency (DTMF) signal) is present within the Sin signal 37. The errorsignal 46 (as is described in further detail in conjunction with FIG. 2)is an intermediate signal within the echo canceller 20. It should benoted that the error signal 46 is not the same as the Sout signal 42,which corresponds to the echo cancelled output of the echo canceller 20.For example, the Sin signal 37 may be a composite signal that includesboth voice and tone components (also referred to as voice informationand tone information, respectively). The tone components may correspondto a single frequency tone and/or multiple frequency tones and areusually referred to as in-band signaling tones. When the tone components(which are in-band with the voice components) are weak, the processingperformed by non-linear processing (NLP) of the echo canceller 20 maydistort the Sout signal 42, such that tone components cannot be easilydetected in the Sout signal 42. According to an aspect of the presentdisclosure, the error signal 46 (which is not processed by the NLP ofthe echo canceller 20) is employed for tone detection. It should beappreciated that the tone detector 50 may correspond to a wide varietyof conventional tone detectors.

The network 24 may correspond to a wide variety of wired networks (e.g.,a public switched telephone network (PSTN)) or wireless networks thatimplement a wide variety of protocols, e.g., voice over internetprotocol (VoIP), data over packet, or asynchronous transfer mode (ATM).As previously noted, the system 10 includes the control 17. In a typicalimplementation, the control 17 provides a control pathway for componentsof the system 10 (i.e., the transmitter/receiver 12 and thetransmitter/receiver 14, the hybrids 16 and 18, the echo cancellers 20and 22, and the network 24). In general, control signals transmitted viathe control 17 do not correspond to in-band signals. For example, thecontrol 17 may include an enabling/disabling signal to enable or disablethe echo cancellers 20 and 22. As another example, the control 17 mayalso include a signal to indicate whether a telephone is on-hook oroff-hook. The tone detectors 50 and 52 may also send messaging signals(via the control 17) to indicate, for example, that one or more toneshave been detected and their corresponding frequency. In the discussionherein, the transmitter/receiver 12 is referred to as the near-end withrespect to echo canceller 20 and the transmitter/receiver 14 is referredto as the far-end with respect to the echo canceller 20. It shouldappreciated that echo canceller 22 operates analogously to the echocanceller 20.

With reference to FIG. 2, the echo canceller 20 of FIG. 1 is furtherillustrated in conjunction with the tone detector 50 of FIG. 1. As isillustrated, the echo canceller 20 includes a direct current (DC) notchfilter 45, an optional non-adaptive filter 31, an adder 34, an optionalnon-adaptive filter 35 (which includes a gain control 33), non-linearprocessor 32, a near-end signal detector 26, an adaptive filter 28, amonitor and control unit (control unit) 30, and a DC notch filter 49. Itshould be appreciated that an echo canceller configured according to thepresent disclosure may include additional (e.g., a pure delay estimator)or fewer components. The DC notch filter 45 receives the Sin signal 37and outputs Sin signal 38 to an input of the near-end signal detector 26and an input of the control unit 30. The Sin signal 38 is also providedto an input of the non-adaptive filter 31, which is coupled to andreceives control signals from the control unit 30. An output of thenon-adaptive filter 31 provides Sin signal 39 to a first input of theadder (combiner) 34. In the event that the non-adaptive filter 31 isomitted, the Sin signal 38 is equivalent to the Sin signal 39.

A second input of the adder 34 receives an echo estimation signal 48(from the adaptive filter 28) and an output of the adder 34 provides theerror signal 46 to an input of the gain control 33, an input of the tonedetector 50, an input of the near-end signal detector 26, and an inputof the control unit 30. An input/output port of the gain control 33 iscoupled to an input/output port of the control unit 30 and an output ofthe gain control 33 provides an error signal 47 to an input of thenon-linear processor 32. In the case where the non-adaptive filter 35 isimplemented in the echo canceller 20, the gain control 33 is implementedwithin the non-adaptive filter 35 (which receives the error signal 46,is bi-directionally coupled to the control unit 30, and provides theerror signal 47). The non-linear processor 32 is bi-directionallycoupled to a port of the control unit 30 and an output of the non-linearprocessor 32 provides the Sout signal 42. The control unit 30 is alsocoupled to the control 17, receives the Rin signal 43, receives an Rinsignal 44 from the DC notch filter 49, and is bi-directionally coupledto the adaptive filter 28 and the near-end signal detector 26. The DCnotch filter 49 receives the Rin signal 43 (which, in the illustratedembodiment, is the same as Rout signal 40) and provides the Rin signal44 to the near-end signal detector 26, the adaptive filter 28, and thecontrol unit 30.

In a typical communication, the Sin signal 37 may include voiceinformation, tone information, and reflected echo from the Rin signal43. It should be appreciated that, in the disclosed embodiment, theerror signal 46 is not sent to the network 24. As discussed above, theSin signal 37 may include reflected echo introduced by the impedancemismatch attributable to the hybrid 16. The echo canceller 20 isconfigured to reduce (or eliminate) the introduced reflected echo andprovides the Sout signal 42. When the impedance in the hybrid 16 isperfectly matched, a signal received at the input of the hybrid 16(i.e., the Rout signal 40) results in virtually no response from thehybrid 16 (in the Sin signal 37) as there is no reflected echo. However,when the hybrid is in an imbalanced state (where the impedance ismismatched), the Rout signal 40 causes a hybrid impulse response (h). Ingeneral, the adaptive filter 28 attempts to imitate the hybrid circuitby producing a replica of the echo signal, which is subtracted from theSin signal 39 (via the adder 34) to produce the error signal 46. Theecho signal (which is equal to the Sin signal 37 when thetransmitter/receiver 12 does not produce any signal, i.e., when the nearend signal, Sgen, is zero, or absent) corresponds to a linearlydistorted Rout signal.

The linear distortions include pure transposition in time, i.e., a shiftin time by a parameter called pure delay, and include other lineardistortions that are related to hybrid dispersion properties. The puredelay refers to the portion of the impulse response from the beginningto where some significant values start to occur. The dispersion timerefers to the portion of the impulse response duration from where thesignificant responses begins to where the responses virtually disappear.The shape of the impulse response (as per the portion corresponding tothe dispersion time segment) can be translated into the frequencycharacteristic of the hybrid (as seen from the Rout signal 40 and theSin signal 37 ports).

The DC notch filter 45 removes the DC component from the Sin signal 37.Similarly, the DC notch filter 49 removes the DC component from the Routsignal 40. In an alternate embodiment, a high-pass filter may be used inplace of one or both of the filters 45 and 49. In general, DC notchfilters (which are usually first-order filters) are computationallycheaper than high-pass filters (which are usually second-order or higherfilters) and produce no rippling effect which helps maintain a flat gainthrough a passband of the filter. In an alternate embodiment, a singleshared DC notch filter may be used to perform the functions of thefilters 45 and 49.

As noted above, the non-adaptive filters 31 and 35 are optional. For thefollowing discussion, an assumption is made that the Sin signal 38 andthe Sin signal 39 are equal and the error signal 47 is a gain adjustedversion of the error signal 46, without the effects of the non-adaptivefilters 31 and 35. In this case, the Sin signal 39 is the send signalwhich includes any near-end signal (Sgen) that is transmitted by thetransmitter of the transmitter/receiver 12 and any reflected echointroduced from the Rout signal 40 (or the Rin signal 43) by the hybrid16. As such, the Sin signal 39 can be expressed as “Sgen+echo”. Itshould be appreciated that the near-end signal (Sgen) may include avoice component (e.g., when a near-end talker is present) and/or one ormore tone components. If both a voice component and one or more tonecomponents are present, then the Sin signal 39 may be considered avoice/tone composite signal. In operation, the adaptive filter 28provides an estimation of the reflected echo (corresponds to the echoestimation signal 48) to the adder 34, which outputs the error signal46.

The error signal 46 can be expressed as ‘Sin signal 39−echo estimationsignal (estimated echo) 48’ or, substituting the above expression forSin 39, as ‘Sgen+echo−estimated echo’. When the estimated echo isaccurate (i.e., equal or substantially equal to the actual echo), thenthe error signal 46 only includes Sgen without any substantial echo.However, if the estimated echo is not accurate, the error signal 46includes both Sgen and a residual echo component. In this case, theerror signal 46 can be expressed as ‘Sgen+residual echo’ where theresidual echo is ‘echo−estimated echo’. When Sgen is absent (i.e., whenthe near-end is silent, meaning no signal is being transmitted from thetransmitter of the transmitter/receiver 12), the error signal 46represents only the residual echo. In this case, the error signal 46 maybe used to perform an adaptive process to minimize the residual echo.However, if Sgen is present, the error signal 46 cannot be used toperform the adaptive process because the adaptive filter 28 uses theerror to adapt, and with the presence of Sgen, the error signal 46 is nolonger just the error. As such, in a typical case, the detection of Sgenis used to determine whether the adaptive process may be performed. Thenear-end signal detector 26 uses the error signal 46 and control signalsfrom the control unit 30 to detect the presence of Sgen (i.e., to detectthe presence of a near-end talker).

In the adaptive filter 28, the echo estimation signal 48, y(k), iscalculated by y(k)=X^(T)(k)·H(k), where X(k)=[x(k), x(k−1), . . . ,x(k−N+1)]^(T) is the input signal vector extending over the duration ofthe finite impulse response (FIR) filter span, x(n) corresponds to theRin signal 44, H(k) is a filter coefficient vector for the kthiteration, where H(k)=[h₀(k), h₁(k), . . . , h_(N-1)(k)]^(T). The actualupdate of the filter coefficients is governed by an implementedalgorithm. As noted above, the implemented algorithm may be virtuallyany application appropriate adaptive filtering algorithm (e.g., anaffine projection (AP) algorithm, a normalized least mean squares (NLMS)algorithm, a least mean squares (LMS) algorithm, or a recursive leastsquares (RLS) algorithm).

Any residual echo in the error signal 46 may be further reduced by thenon-linear processor 32. The non-linear processor 32 receives the errorsignal 47 (which corresponds to a gain adjusted version of the errorsignal 46) and control signals from the control unit 30 to produce Sout42, which, ideally, includes no echo and is provided as an output ofecho canceller 20 to the network 24. Unfortunately, the non-linearprocessing performed by non-linear processor 32 introduces distortioninto the Sout signal 42. As such, when the Sout signal 42 is avoice/tone composite signal including both voice and tone components,the distortion by non-linear processor 32 may make the tone componentsdifficult to detect. According to an aspect of the present disclosure,the error signal 46 is provided to the tone detector 50 to facilitateimproved detection of tone components. In this manner, the tone detector50 can operate on a less distorted signal (i.e., the error signal 46instead of the Sout signal 42).

The control unit 30 may implement a filter coefficient monitor which isused to determine whether a true hybrid exists such that adaptive filter28 does not attempt to adapt to invalid hybrids. The control unit 30 mayalso include a gain monitor to control the gain control 33 (within theadaptive filter 35) and facilitate maintaining stability of the system10. The control unit 30 may also include a tone indicator and a tonedetector for use in controlling the adaptive filter 35. The toneindicator and tone detector may be used to detect signaling tones withinthe system 10. For example, the signaling tones may include a 2100 Hztone with a phase reversal for disabling the echo canceller when data isto be sent following the signaling tone. As mentioned above, disablingthe echo canceller 20 prevents the adaptive filter 28 from diverging andcausing instability in the system 10. When implemented, the non-adaptivefilter 31 can be used to reduce the length of the adaptive filter 28 andthe non-adaptive filter 35 compensates for the effects of thenon-adaptive filter 31, such that the near-end signal Sgen is notdistorted.

In the case of composite signals having both voice and tone components,the non-linear processor tends to introduce distortions, such astemporal clipping and/or attenuation. In at least one embodiment, anecho canceller allows for integrated tone detector capabilities by usingan intermediate signal (i.e., the error signal 46) within the echocanceller 20 for tone detection rather than the Sout signal 42 of theecho canceller 20.

Moving to FIG. 3, an example process 300 for updating filtercoefficients of an adaptive filter, according to one or more embodimentsof the present disclosure, is illustrated. The adaptive filter may, forexample, be included in an echo canceller and be utilized to reduce (oreliminate) an echo signal. The process 300 is initiated in block 302 atwhich point control transfers to block 304, where the adaptive filter issegmented into filter blocks, each including one or more filtercoefficients. In general, the number and size of the blocks may vary, aslong as the number and size of the blocks facilitates updating blockswith higher metrics more often than blocks with lower metrics. In atypical case, an adaptive filter is segmented into two or more filterblocks and a size of a given one of the blocks may be chosen based onthe values of the filter coefficients of the adaptive filter. As oneexample, an adaptive filter may be segmented into first, second, andthird blocks. Next, in block 306, filter coefficients are grouped intothe filter blocks. In various embodiments, the filter coefficients maybe grouped into the filter blocks based on a network echo path impulseresponse. In a usual case, during the adaptation process, when theadaptive filter converges (i.e., when filter coefficients of theadaptive filter better resemble filter coefficients of a linear model ofan echo path impulse response), the filter coefficients can be analyzedin real-time.

During real-time analysis, filter coefficient can be grouped into blocksbased on various metrics (e.g., absolute value, magnitude, or energy).As one example, some of the filter coefficients may have relativelylarge values and other of the filter coefficients may have relativelysmall values. According to the present disclosure, the process ofdetermining a metric of the filter coefficient is implemented inreal-time. For example, the grouping of the filter coefficients intoblocks may be based on magnitudes of the filter coefficients through acomparison of peak values.

For example, assuming an adaptive filter has only eight filtercoefficients and after an initial adaptation the filter coefficients(which values typically start with an initial condition of zero) achievethe following values: 0; −0.01; 0.2; 0.5; 0.1; −0.1; 0.01; and −0.01. Inthis case, a maximum filter coefficient value is 0.5. Assuming thefilter coefficients are grouped into three blocks, a first block mayinclude the filter coefficient values [0, −0.01], a second block mayinclude the filter coefficient values [0.01, −0.01], and a third blockmay include the filter coefficient values [0.2; 0.5; 0.1; −0.1]. In thisexample, the coefficient values of the first and second blocks aresignificantly smaller than the maximum filter coefficient value of 0.5.In this case, according to the present disclosure, the first and secondblocks (corresponding to filter coefficient indices 1, 2, 7, and 8) areupdated less often than the third block (corresponding to the filtercoefficient indices 3, 4, 5, and 6). It should be appreciated that thepartitioning of filter coefficients into filter blocks may be based onvarious criteria. For example, filter coefficients that have values often percent or less of a maximum filter coefficient value can beconsidered as sufficiently small and updated less often than otherfilter coefficients. As another example, only those filter coefficientsthat are at least five percent or more of a maximum filter coefficientmagnitude may be updated each input sample of an echo signal.

Then, in block 308, the filter coefficients for less than all of thefilter blocks are updated each update period. In general, filtercoefficients with lower/smaller metrics are updated less often thanfilter coefficients with higher/larger metrics. For example, filtercoefficients for filter blocks that exhibit a higher energy, a higherabsolute value, or a higher magnitude are updated more frequently thanfilter coefficients for filter blocks that exhibit a lower energy, alower absolute value, or a lower magnitude, respectively.

As one example, when the adaptive filter is segmented into the first,second, and third blocks: the filter coefficients for the first blockmay be updated for each input sample (assumes that the first block hasmore significant filter coefficients that the second and third blocks);the filter coefficients for the second block may be updated for oddinput samples, and the filter coefficients for the third block may beupdated for even input samples. As another example, the first block mayinclude ninety-six of the filter coefficients, the second block mayinclude forty-eight of the filter coefficients, and the third block mayinclude forty-eight of the filter coefficients. As yet another example,the first, second, and third blocks may each include sixty-four filtercoefficients. Next, in block 309, the echo signal is filtered with theconverged segmented adaptive filter. Following block 309, controltransfers to block 310, where the process 300 terminates and controlreturns to a calling process.

In general, most significant filter coefficients are located in abeginning portion of an adaptive filter when estimation of a pure delayvalue is adequate. Accordingly, an adaptive filter is segmented into ‘N’filter blocks (N≦K, where ‘K’ is the number of FIR filter coefficients).For each iteration, only ‘M’ (M<N) filter blocks are selected to beupdated and filter coefficients in unselected blocks remain unchanged.As noted above, the choice of filter blocks is usually dependent on thecharacteristics of the specified network echo path model. The generalidea is that the filter blocks with more significant filter coefficientvalues are updated more frequently than filter coefficients belonging tofilter blocks with less significant filter coefficient values. As only aportion of the filter coefficients are updated each sample, lesscomputational power is required.

As may be used herein, a software system can include one or moreobjects, agents, threads, subroutines, separate software applications,two or more lines of code or other suitable software structuresoperating in one or more separate software applications, on one or moredifferent processors, or other suitable software architectures.

As will be appreciated, the processes in various embodiments of thepresent invention may be implemented using any combination of software,firmware or hardware. As a preparatory step to practicing the inventionin software, code (whether software or firmware) according to apreferred embodiment will typically be stored in one or more machinereadable storage mediums such as semiconductor memories such asread-only memories (ROMs), programmable ROMs (PROMs), etc., therebymaking an article of manufacture in accordance with the invention. Thearticle of manufacture containing the code is used by either executingthe code directly from the storage device or by copying the code fromthe storage device into another storage device such as a random accessmemory (RAM), etc. An apparatus for practicing the techniques of thepresent disclosure could be one or more communication devices.

Although the invention is described herein with reference to specificembodiments, various modifications and changes can be made withoutdeparting from the scope of the present invention as set forth in theclaims below. For example, the techniques disclosed herein are generallybroadly applicable to wired and wireless communication systems thatfacilitate voice communication, in addition to data communication.Accordingly, the specification and figures are to be regarded in anillustrative rather than a restrictive sense, and all such modificationsare intended to be included with the scope of the present invention. Anybenefits, advantages, or solution to problems that are described hereinwith regard to specific embodiments are not intended to be construed asa critical, required, or essential feature or element of any or all theclaims.

Unless stated otherwise, terms such as “first” and “second” are used toarbitrarily distinguish between the elements such terms describe. Thus,these terms are not necessarily intended to indicate temporal or otherprioritization of such elements.

1. A method for updating filter coefficients of an adaptive filter,comprising: filtering a signal with an adaptive filter whose filtercoefficients are grouped into filter blocks, wherein a number of thefilter blocks is less than or equal to a number of the filtercoefficients; and updating, during each update period, the filtercoefficients for less than all of the filter blocks based on a networkecho path impulse response.
 2. The method of claim 1, furthercomprising: segmenting the adaptive filter into filter blocks based onvalues of the filter coefficients.
 3. The method of claim 1, wherein theupdating further comprises: updating the filter coefficients for thefilter blocks that exhibit a higher energy more frequently than thefilter coefficients for the filter blocks that exhibit a lower energy.4. The method of claim 1, wherein the updating further comprises:updating the filter coefficients for the filter blocks that exhibit alarger absolute value more frequently than the filter coefficients forthe filter blocks that exhibit a lower absolute value.
 5. The method ofclaim 1, wherein the updating further comprises: updating the filtercoefficients for the filter blocks that exhibit a higher magnitude morefrequently than the filter coefficients for the filter blocks thatexhibit a lower magnitude.
 6. The method of claim 1, wherein a length ofthe filter blocks is the same.
 7. The method of claim 1, wherein alength of at least two of the filter blocks is different.
 8. The methodof claim 1, wherein the filter blocks includes first, second, and thirdblocks, and wherein the filter coefficients in the first block have ahigher energy, absolute value, or magnitude than the filter coefficientsin the second and third blocks and the updating further comprises:updating, for each input sample of the signal, the filter coefficientsfor the first block; updating, for odd input samples of the signal, thefilter coefficients for the second block; and updating, for even inputsamples of the signal, the filter coefficients for the third block. 9.The method of claim 1, wherein the adaptive filter implements an affineprojection (AP) algorithm, a normalized least mean squares (NLMS)algorithm, a least mean squares (LMS) algorithm, or a recursive leastsquares (RLS) algorithm during the updating of the filter coefficients.10. The method of claim 1, further comprising: grouping the filtercoefficients into the filter blocks based on the network echo pathimpulse response.
 11. The method of claim 1, wherein the signal is anecho signal and the adaptive filter is configured to reduce the echosignal.
 12. A communication device, comprising: a control module; and anadaptive filter in communication with the control module, wherein theadaptive filter is configured to filter a signal and is segmented intofilter blocks, and wherein a number of the filter blocks is less than orequal to a number of filter coefficients for the adaptive filter, thefilter coefficients are grouped into the filter blocks based on anetwork echo path impulse response, and, during each update period, thefilter coefficients for less than all of the filter blocks are updated.13. The communication device of claim 12, wherein the filtercoefficients for the filter block that exhibits a highest energy isupdated more frequently than the filter coefficients for the filterblocks that exhibit a lower energy.
 14. The communication device ofclaim 12, wherein the filter coefficients for the filter block thatexhibits a larger magnitude is updated more frequently than the filtercoefficients for the filter blocks that exhibit a smaller magnitude. 15.The communication device of claim 12, wherein the filter coefficientsfor the filter block that exhibits a highest absolute value is updatedmore frequently than the filter coefficients for the filter blocks thatexhibit a lower absolute value.
 16. The communication device of claim12, wherein a length of the filter blocks is the same.
 17. Thecommunication device of claim 12, wherein a length of at least two ofthe filter blocks is different.
 18. The communication device of claim12, wherein the signal is an echo signal and the communication device isan echo canceller.
 19. A method for updating filter coefficients of anadaptive filter of an echo canceller, comprising: filtering an echosignal with an adaptive filter whose filter coefficients are groupedinto filter blocks based on a network echo path impulse response,wherein a number of the filter blocks is less than or equal to a numberof the filter coefficients; and updating, during each update period, thefilter coefficients for less than all of the filter blocks based on ametric associated with the filter coefficients.
 20. The method of claim19, wherein a length of at least two of the filter blocks is different.